Fault Detection of Unmanned Surface Vehicles Based on Dynamic Event-Triggered Mechanism under Hybrid Network Attacks

With the rapid development of the internet of things, cloud computing, and artificial intelligence, the cybersecurity and fault issues of networked systems have become key research topics. This paper investigates the fault detection and filtering problem for unmanned surface vehicles (USVs) under hybrid network attacks, external disturbances, and faults, based on a dynamic event-triggered mechanism (DETM). An H<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</inf> filter with a fault detection mechanism is designed to detect system faults using residual signals, ensuring the normal operation of the system. Furthermore, a DETM is proposed to reduce the transmission frequency of information in the channel and mitigate the adverse effects of hybrid attacks. Third, a time-delay residual system model is constructed, and the criteria for the system’s mean square exponential stability and H<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</inf> performance are derived using a piecewise Lyapunov function, along with a comprehensive design approach. Finally, simulation results are provided to validate the effectiveness of the proposed dynamic event-triggered fault detection method.